University of Technology Sydney

36106 Machine Learning Algorithms and Applications

8cp; block mode with weekly online work, 1 Wednesday evening and 4 Saturday sessions online or on campus; availability: Master of Data Science and Innovation and Master of Business Analytics students
There are course requisites for this subject. See access conditions.
Anti-requisite(s): 36113 Applied Data Science for Innovation AND 36114 Advanced Data Science for Innovation

Requisite elaboration/waiver:

Any student wishing to enrol in first- and second-year subjects concurrently must apply for a waiver.



This subject introduces students to key machine learning algorithms and their application in real-world settings. Participants are guided in developing an intuitive understanding of how the algorithms work, as well as their strengths and weaknesses. In addition to gaining practical experience with the algorithms, students develop an understanding of the basic principles of machine learning and the connections between different algorithms. Additionally, they are exposed to industry standard methodologies for data mining and analytics via readings and assessments. Since data science problems are infused with assumptions, often with ethical and legal implications, due attention is given to questioning the assumptions behind data and approaches used to analyse it.

Typical availability

Autumn session, City campus

Detailed subject description.

Access conditions

Note: The requisite information presented in this subject description covers only academic requisites. Full details of all enforced rules, covering both academic and admission requisites, are available at access conditions and My Student Admin.